import pandas as pd
from text_normalizer import normalizer
import json
"""word_enter_charachters = {"^p","'^l'"}"""
def read_excel_file(file_path):
    """
    Reads an Excel file and returns a list of dictionaries containing the data.
    """
    data = pd.read_excel(file_path)
    bime_json_list = []
    count = 0
    for row in data.itertuples():
        
        if count == 102:
            pass

        radif = normalizer.normalize_qanon(row[1]).replace('.','')
        if radif == "":
            radif = bime_json_list[count-1]['radif']
            
        qanon_title = normalizer.normalize_qanon(row[2]).replace('.','').replace('#!#',' ').strip()
        if qanon_title == "":
            qanon_title = bime_json_list[count-1]['qanon_title']
            
        related = normalizer.normalize_qanon(row[3]).replace('.','')
        if related == "":
            related = bime_json_list[count-1]['related']
            
        row_structure = {
            "id": row[0],
            "radif":radif,
            "qanon_title": qanon_title,
            "related": related,
            "status": normalizer.normalize_qanon(row[4]).replace('#!#',''),
            "reasons": normalizer.normalize_qanon(row[5]).replace('#!#','\n'),
            "description": normalizer.normalize_qanon(row[6]),
        }
        bime_json_list.append(row_structure)
        count += 1
        
        
    return bime_json_list

def write_to_json(data_dict, output_path):
    """
    Writes data to a JSON file.
    """
    with open(output_path, 'w', encoding='utf-8') as json_file:
        json.dump(data_dict, json_file, indent=4, ensure_ascii=False)  
        
    return True    
        
if __name__ == '__main__':
    data_dict = read_excel_file('./data/bime.xlsx')
    write_to_json(data_dict, './data/bime.json')
    print('Done!')